Alongside-team·6 days ago
6 days ago
Senior Machine Learning Engineer
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What you'll do
- Design, develop, and maintain scalable data and end-to-end ML pipelines, from data ingestion to production deployment.
- Build and deploy ML services and APIs, ensuring reliability, scalability, and performance.
- Partner with Data Scientists to transform models into robust, production-ready solutions.
- Implement MLOps best practices, including CI/CD, testing, data/code quality, monitoring, and model lifecycle management.
- Troubleshoot production ML systems and drive technical and architectural decisions.
- Work with AWS ML services, particularly SageMaker, and containerized environments using Docker/Kubernetes.
- Contribute to GenAI implementations within our platform framework.
- Mentor team members and contribute to delivery in an Agile/Scrum environment.
What they're looking for
- Degree in Computer Engineering, IT, or a related field.
- 5+ years of experience in Backend Engineering and/or Machine Learning Engineering.
- Strong production-level Python development skills.
- Hands-on experience building E2E ML pipelines and deploying ML models through APIs.
- Experience with SQL/NoSQL databases, testing frameworks, and data/code quality practices.
- Experience with MLOps tools such as MLflow, Kubeflow, or similar.
- Strong knowledge of AWS, particularly SageMaker and related ML services.
- Experience with Docker and Kubernetes.
- Strong understanding of ML model deployment and lifecycle management.
- Fluent English and strong communication and technical decision-making skills.
Nice to have
- Experience with Computer Vision, NLP, TensorFlow/PyTorch, Scikit-Learn, Pandas, Terraform/CloudFormation, asynchronous messaging, and ML monitoring/observability tools.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Alongside is a Portuguese company that partners with international organizations to build and scale exceptional tech teams.
We are looking for a Senior Machine Learning Engineer to join a project with one of our clients, a global leader in professional information solutions and software. Operating across more than 180 countries, the company develops technology-driven solutions for industries including Healthcare, Tax & Accounting, Financial & Corporate Compliance, and Legal & Regulatory.
Responsibilities:
- Design, develop, and maintain scalable data and end-to-end ML pipelines, from data ingestion to production deployment.
- Build and deploy ML services and APIs, ensuring reliability, scalability, and performance.
- Partner with Data Scientists to transform models into robust, production-ready solutions.
- Implement MLOps best practices, including CI/CD, testing, data/code quality, monitoring, and model lifecycle management.
- Troubleshoot production ML systems and drive technical and architectural decisions.
- Work with AWS ML services, particularly SageMaker, and containerized environments using Docker/Kubernetes.
- Contribute to GenAI implementations within our platform framework.
- Mentor team members and contribute to delivery in an Agile/Scrum environment.
Requirements
- Degree in Computer Engineering, IT, or a related field.
- 5+ years of experience in Backend Engineering and/or Machine Learning Engineering.
- Strong production-level Python development skills.
- Hands-on experience building E2E ML pipelines and deploying ML models through APIs.
- Experience with SQL/NoSQL databases, testing frameworks, and data/code quality practices.
- Experience with MLOps tools such as MLflow, Kubeflow, or similar.
- Strong knowledge of AWS, particularly SageMaker and related ML services.
- Experience with Docker and Kubernetes.
- Strong understanding of ML model deployment and lifecycle management.
- Fluent English and strong communication and technical decision-making skills.
Nice to Have - Experience with Computer Vision, NLP, TensorFlow/PyTorch, Scikit-Learn, Pandas, Terraform/CloudFormation, asynchronous messaging, and ML monitoring/observability tools.
Benefits
- Hybrid working model: 2 days per week at the office (Porto);
- Collaborative and international work environment;
- Opportunity to work on impactful software products and transformation projects;
- Exposure to modern technologies, tools, and development practices;
- Opportunity to collaborate with experienced professionals across different countries and areas of expertise.
Company
Alongside-team
Porto, Portugal
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